I read the study, it's a few pages-long PDF with no description of computational methodology, no indication of the statistical approaches taken, and no justification for the arbitrary decisions made by the people who carried out the study.
The criteria for inclusion in the study:
> Hospitalized adults aged ≥18 years with COVID-19–like illness were included if they had received testing at least twice: once associated with a COVID-19–like illness hospitalization during January–September 2021 and at least once earlier (since February 1, 2020, and ≥14 days before that hospitalization).
This is a terrible methodology. It says nothing of a positive or negative test result, and the duration of time in between hospitalization and testing is absurdly arbitrary. It is simply assumed to be a COVID infection with no reasoning for this decision.
We've then got this nugget:
> Laboratory-confirmed SARS-CoV-2 infection was identi-fied among 324 (5.1%) of 6,328 fully vaccinated persons and among 89 of 1,020 (8.7%) unvaccinated, previously infected persons
Perhaps they should have found 5,000 more unvaccinated people before concluding their study. They are not hard to find.
> Do you genuinely believe a study with such a massive and obvious methodology problem would get published and cited by the CDC?
This is a joke, right? The CDC are frequently derided for their terrible methodologies and this goes back for decades. Not an uncommon outcome where you are an inherently political organization that is also in charge of distributing enormous sums for research funding. So of course, I would expect a terrible study like this from the CDC.
You're actually going to compare this crap-tastic shitfest of a study with the rock-solid study I provided, containing ~3mil participants and a far more verbose & informative outline of the study's methodology?